Evidence map›Paper›PMID 39133767›Full record

ReviewJournal of magnetic resonance imaging : JMRI2025

State-of-the-Art Quantification of Liver Iron With MRI-Vendor Implementation and Available Tools.

Aaryani Tipirneni-Sajja, Utsav Shrestha, Juan Esparza, Cara E Morin, Stephan Kannengiesser, Nathan T Roberts, Johannes M Peeters, Samir D Sharma, Houchun H Hu

Abstract readReview
In one paragraph

Review in Journal of magnetic resonance imaging : JMRI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Aaryani Tipirneni-SajjaDepartment of Biomedical Engineering, The University of Memphis, Memphis, Tennessee, USA.ORCID https://orcid.org/0000-0002-3246-8711
Utsav ShresthaDepartment of Biomedical Engineering, The University of Memphis, Memphis, Tennessee, USA.
Juan EsparzaDepartment of Biomedical Engineering, The University of Memphis, Memphis, Tennessee, USA.
Cara E MorinDepartment of Radiology, Cincinnati Children's Hospital, Cincinnati, Ohio, USA.ORCID https://orcid.org/0000-0003-1953-4486
Stephan KannengiesserMR Applications Predevelopment, Siemens Healthineers AG, Erlangen, Germany.
Nathan T RobertsMR Clinical Solutions & Research Collaborations, GE HealthCare, Waukesha, Wisconsin, USA.
Johannes M PeetersMR Clinical Science, Philips, Best, The Netherlands.
Samir D SharmaCanon Medical Research USA, Inc., Mayfield Village, Ohio, USA.
Houchun H HuRadiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.

Funding

MODELING MRI-BASED TISSUE RELAXATION IN THE PRESENCE OF IRON OVERLOAD AND STEATOSISR21EB031298 · NIBIB · UNIVERSITY OF MEMPHIS · PI TIPIRNENI-SAJJA, AARYANI · 2021 to 2022
$589k
NIBIB NIH HHS R21 EB031298NIBIB NIH HHS R21EB031298
6 · The paper itself

Abstract

The role of MRI to estimate liver iron concentration (LIC) for identifying patients with iron overload and guiding the titration of chelation therapy is increasingly established for routine clinical practice. However, the existence of multiple MRI-based LIC quantification techniques limits standardization and widespread clinical adoption. In this article, we review the existing and widely accepted MRI-based LIC estimation methods at 1.5 T and 3 T: signal intensity ratio (SIR) and relaxometry (R2 and R2*) and discuss the basic principles, acquisition and analysis protocols, and MRI-LIC calibrations for each technique. Further, we provide an up-to-date information on MRI vendor implementations and available offline commercial and free software for each MRI-based LIC quantification approach. We also briefly review the emerging and advanced MRI techniques for LIC estimation and their current limitations for clinical use. Lastly, we discuss the implications of MRI-based LIC measurements on clinical use and decision-making in the management of patients with iron overload. Some of the key highlights from this review are as follows: 1) Both R2 and R2* can estimate accurate and reproducible LIC, when validated acquisition parameters and analysis protocols are applied, 2) Although the Ferriscan R2 method has been widely used, recent consensus and guidelines endorse R2*-MRI as the most accurate and reproducible method for LIC estimation, 3) Ongoing efforts aim to establish R2*-MRI as the standard approach for quantifying LIC, and 4) Emerging R2*-MRI techniques employ radial sampling strategies and offer improved motion compensation and broader dynamic range for LIC estimation. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Indexed as

IronIron OverloadLiverMagnetic Resonance ImagingHumansImage Processing, Computer-AssistedReproducibility of ResultsSoftwareIroniron overloadLICR2R2*softwarevendor

Identifiers

PMID39133767
PMCPMC12145509

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.